CUDA Toolkit
The NVIDIA® CUDA® Toolkit provides a development environment for creating high-performance, GPU-accelerated applications. With it, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library.
The Features of CUDA 12
Built-In Capabilities for Easy Scaling
Using built-in capabilities for distributing computations across multi-GPU configurations, you can develop applications that scale from single-GPU workstations to cloud installations with thousands of GPUs.
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New Release, New Benefits
CUDA 12 introduces support for the NVIDIA Hopper™ and Ada Lovelace architectures, Arm® server processors, lazy module and kernel loading, revamped dynamic parallelism APIs, enhancements to the CUDA graphs API, performance-optimized libraries, and new developer tool capabilities.
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Support for Hopper
Support for the Hopper architecture includes next-generation Tensor Cores and Transformer Engine, the high-speed NVIDIA NVLink® Switch, mixed-precision modes, second-generation Multi-Instance GPU (MIG), advanced memory management, and standard C++/Fortran/Python parallel language constructs.
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Tutorials
CUDA Developer Tools is a series of tutorial videos designed to get you started using NVIDIA Nsight™ tools for CUDA development. It explores key features for CUDA profiling, debugging, and optimizing.
CUDA Compatibility
Watch VideoCUDA Upgrades for Jetson Devices
Watch VideoProfiling and Debugging Applications
Watch VideoInstalling CUDA Toolkit on Windows and WSL
Watch VideoGTC Digital Webinars
Dive deeper into the latest CUDA features.
Inside the NVIDIA Hopper Architecture
Explore what's new with the NVIDIA Hopper architecture and its implementation in the NVIDIA H100 Tensor Core GPU.
Watch NowCUDA—New Features and Beyond
Learn what's new in the CUDA Toolkit, including the latest and greatest features in the CUDA language, compiler, libraries, and tools—and get a sneak peek at what's coming up over the next year.
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CUDA on NVIDIA Hopper GPU Architecture
Learn how to leverage the NVIDIA Hopper architecture’s capabilities to take your algorithms to the next level of performance.
Watch NowCustomer Stories
See how developers, scientists, and researchers are using CUDA today.
Using HPC to Explore the Universe
Wes Armour, director at the Oxford e-Research Centre, discusses the role of GPUs in processing large amounts of astronomical data collected by the Square Kilometre Array and how CUDA is the best-suited option for their signal processing software.
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Opening a New Era of Drug Discovery With Amber
David Cerutti and Taisung Lee from Rutgers University share how Amber, harnessing CUDA, is advancing multiple scientific domains and opening a new era of drug discovery and design.
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Visualizing and Simulating Atomic Structures
John Stone, senior research programmer at the Beckman Institute at the University of Illinois, Urbana-Champaign, discusses how CUDA and GPUs are used to process large datasets to visualize and simulate high-resolution atomic structures.
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CUDA Ecosystem
Explore the top compute and graphics packages with built-in CUDA integration.
Featured Blogs
Content Moderation and Safety Checks with NVIDIA NeMo Guardrails
Content moderation has become essential in retrieval-augmented generation (RAG) applications powered by generative AI, given the extensive volume of user-generated content and external data that these systems manage. RAG-based applications use large language models (LLMs) along with real-time information retrieval from various external sources, which can lead to a more dynamic and unpredictable flow of … Continued
Celebrating Open Science and Enterprise AI Innovation on MONAI’s 5th Anniversary
As MONAI celebrates its fifth anniversary, we’re witnessing the convergence of our vision for open medical AI with production-ready enterprise solutions. This announcement brings two exciting developments: the release of MONAI Core v1.4, expanding open-source capabilities, and the general availability of VISTA-3D and MAISI as NVIDIA NIM microservices. This dual release reflects our commitment to … Continued
Unified Virtual Memory Supercharges pandas with RAPIDS cuDF
cuDF-pandas, introduced in a previous post, is a GPU-accelerated library that accelerates pandas to deliver significant performance improvements—up to 50x faster—without requiring any changes to your existing code. As part of the NVIDIA RAPIDS ecosystem, cuDF-pandas acts as a proxy layer that executes operations on the GPU when possible, and falls back to the CPU … Continued
Optimize GPU Workloads for Graphics Applications with NVIDIA Nsight Graphics
One of the great pastimes of graphics developers and enthusiasts is comparing specifications of GPUs and marveling at the ever-increasing counts of shader cores, RT cores, teraflops, and overall computational power with each new generation. Achieving the maximum theoretical performance represented by those numbers is a major focus in the world of graphics programming. Massive … Continued
Latest News
Just Released: NVIDIA Modulus v24.12
The new release includes new network architectures for external aerodynamics application as well as for climate and weather prediction.
Upcoming Webinar: Enhance Generative AI Model Accuracy Through High-Quality Data Processing
Learn how to build scalable data processing pipelines to create high-quality datasets.
NVIDIA Showcases the Future of Intelligent Robots at CoRL 2024
From humanoids to policy, explore the work NVIDIA is bringing to the robotics community.
Powering the Next Wave of AI Robotics with Three Computers
NVIDIA has built three computers and accelerated development platforms to enable developers to create physical AI.
Free Tools and Trainings for Developers
Get exclusive access to hundreds of SDKs, technical trainings, and opportunities to connect with millions of like-minded developers, researchers, and students.
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Resources
CUDA Documentation and Release Notes
Documentation library containing in-depth technical information on the CUDA Toolkit.
CUDA 12 Features Revealed
A technical blog on the CUDA Toolkit 12.0’s features and capabilities.
CUDA Toolkit in the NGC Catalog
CUDA containers are available to download from NGC™—along with other NVIDIA GPU-accelerated SDKs and AI models—to help accelerate your applications.
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All CUDA Technical Blogs
An archive of CUDA technical blogs covering key features and capabilities, written by engineers for engineers.
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CUDA-X™ Libraries
A suite of AI, data science, and math libraries developed to help developers accelerate their applications.
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Training
Self-paced or instructor-led CUDA training courses for developers through the NVIDIA Deep Learning Institute (DLI).
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Nsight Developer Tools
NVIDIA Nsight Compute and Nsight System suite of tools designed to help developers optimize and increase performance of their applications.
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Sample CUDA Code
GitHub repository of sample CUDA code to help developers learn and ramp up development of their GPU-accelerated applications.
NVIDIA Developer Forums
An information exchange to help developers get answers to their technical questions directly from NVIDIA engineers.
Bug Submission
NVIDIA Engineering’s own bug tracking tool and database where developers can submit technical bugs.
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